To use incense we first have to instantiate an experiment loader that will enable us to query the database for specific runs.
| targets_type | iteration | autoencoder_type | batch_size | artifacts | |
|---|---|---|---|---|---|
| exp_id | |||||
| 1 | 10_Targets | False | Over_dim | 256 | {'history_autoencoder': Artifact(name=history_... |
| 2 | 10_Targets | False | Over_dim | 128 | {'history_autoencoder': Artifact(name=history_... |
| 3 | 10_Targets | False | Over_dim | 64 | {'history_autoencoder': Artifact(name=history_... |
| 4 | 10_Targets | False | Over_dim | 32 | {'history_autoencoder': Artifact(name=history_... |
| 5 | Mnist | False | Over_dim | 256 | {'history_autoencoder': Artifact(name=history_... |
| 6 | Mnist | False | Over_dim | 128 | {'history_autoencoder': Artifact(name=history_... |
| 7 | Mnist | False | Over_dim | 64 | {'history_autoencoder': Artifact(name=history_... |
| 8 | Mnist | False | Over_dim | 32 | {'history_autoencoder': Artifact(name=history_... |
| 66 | Noisy | False | Over_dim | 256 | {'history_autoencoder': Artifact(name=history_... |
| 67 | Noisy | False | Over_dim | 128 | {'history_autoencoder': Artifact(name=history_... |
| 68 | Noisy | False | Over_dim | 64 | {'history_autoencoder': Artifact(name=history_... |
| 69 | Noisy | False | Over_dim | 32 | {'history_autoencoder': Artifact(name=history_... |
| targets_type | iteration | autoencoder_type | batch_size | artifacts | |
|---|---|---|---|---|---|
| exp_id | |||||
| 1 | 10_Targets | False | Over_dim | 256 | {'history_autoencoder': Artifact(name=history_... |
| 2 | 10_Targets | False | Over_dim | 128 | {'history_autoencoder': Artifact(name=history_... |
| 3 | 10_Targets | False | Over_dim | 64 | {'history_autoencoder': Artifact(name=history_... |
| 4 | 10_Targets | False | Over_dim | 32 | {'history_autoencoder': Artifact(name=history_... |
| 5 | Mnist | False | Over_dim | 256 | {'history_autoencoder': Artifact(name=history_... |
| 6 | Mnist | False | Over_dim | 128 | {'history_autoencoder': Artifact(name=history_... |
| 7 | Mnist | False | Over_dim | 64 | {'history_autoencoder': Artifact(name=history_... |
| 8 | Mnist | False | Over_dim | 32 | {'history_autoencoder': Artifact(name=history_... |
| 66 | Noisy | False | Over_dim | 256 | {'history_autoencoder': Artifact(name=history_... |
| 67 | Noisy | False | Over_dim | 128 | {'history_autoencoder': Artifact(name=history_... |
| 68 | Noisy | False | Over_dim | 64 | {'history_autoencoder': Artifact(name=history_... |
| 69 | Noisy | False | Over_dim | 32 | {'history_autoencoder': Artifact(name=history_... |
Red best overall, and also best of subset. Bes means for accuracy max, rest min. Green best of subset.
predictions_df_0
| Over_dim 256 10_Targets | Over_dim 128 10_Targets | Over_dim 64 10_Targets | Over_dim 32 10_Targets | Over_dim 256 Mnist | Over_dim 128 Mnist | Over_dim 64 Mnist | Over_dim 32 Mnist | Over_dim 256 Noisy | Over_dim 128 Noisy | Over_dim 64 Noisy | Over_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.9859 | 0.9851 | 0.9839 | 0.976 | 0.9774 | 0.9801 | 0.9774 | 0.9779 | 0.9705 | 0.9708 | 0.9703 | 0.9678 |
| 1 | 0.9834 | 0.9838 | 0.982 | 0.9725 | 0.9736 | 0.9752 | 0.9751 | 0.9736 | 0.9616 | 0.9586 | 0.9559 | 0.9495 |
| 2 | 0.9832 | 0.9837 | 0.982 | 0.9726 | 0.9675 | 0.9658 | 0.9632 | 0.9608 | 0.9453 | 0.9443 | 0.9293 | 0.922 |
| 3 | 0.9832 | 0.9837 | 0.982 | 0.9726 | 0.9516 | 0.9495 | 0.9457 | 0.9436 | 0.924 | 0.9214 | 0.9027 | 0.8887 |
| 4 | 0.9832 | 0.9837 | 0.982 | 0.9726 | 0.9334 | 0.93 | 0.9188 | 0.9212 | 0.9025 | 0.8985 | 0.8713 | 0.8522 |
| 5 | 0.9832 | 0.9837 | 0.982 | 0.9726 | 0.9128 | 0.9058 | 0.8892 | 0.8938 | 0.8774 | 0.8728 | 0.8429 | 0.8157 |
| 6 | 0.9832 | 0.9837 | 0.982 | 0.9726 | 0.882 | 0.8786 | 0.8516 | 0.862 | 0.8515 | 0.846 | 0.8163 | 0.7749 |
| 7 | 0.9832 | 0.9837 | 0.982 | 0.9726 | 0.8474 | 0.8481 | 0.81 | 0.8332 | 0.8266 | 0.8175 | 0.7883 | 0.7393 |
| Over_dim 256 10_Targets | Over_dim 128 10_Targets | Over_dim 64 10_Targets | Over_dim 32 10_Targets | Over_dim 256 Mnist | Over_dim 128 Mnist | Over_dim 64 Mnist | Over_dim 32 Mnist | Over_dim 256 Noisy | Over_dim 128 Noisy | Over_dim 64 Noisy | Over_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.405846 | 0.407413 | 0.407909 | 0.412037 | 0.0201405 | 0.0284971 | 0.0296224 | 0.0304359 | 0.651912 | 0.65597 | 0.657636 | 0.657051 |
| 1 | 0.408316 | 0.410232 | 0.411725 | 0.415863 | 0.0325913 | 0.0427956 | 0.0470546 | 0.047489 | 0.668866 | 0.673641 | 0.678579 | 0.678597 |
| 2 | 0.408536 | 0.41057 | 0.412104 | 0.416526 | 0.0485427 | 0.0608086 | 0.0684454 | 0.0678358 | 0.686306 | 0.691416 | 0.69903 | 0.700124 |
| 3 | 0.408547 | 0.41058 | 0.412137 | 0.416546 | 0.0666118 | 0.0804393 | 0.0912556 | 0.089255 | 0.703317 | 0.708342 | 0.717903 | 0.719993 |
| 4 | 0.408547 | 0.410582 | 0.412138 | 0.416559 | 0.0859192 | 0.100838 | 0.114288 | 0.110792 | 0.719602 | 0.724105 | 0.73502 | 0.73781 |
| 5 | 0.408547 | 0.410582 | 0.412138 | 0.416558 | 0.10589 | 0.121137 | 0.136986 | 0.132799 | 0.735017 | 0.738669 | 0.750456 | 0.753728 |
| 6 | 0.408547 | 0.410582 | 0.412138 | 0.416559 | 0.126183 | 0.141152 | 0.158792 | 0.153934 | 0.749489 | 0.752109 | 0.764484 | 0.767921 |
| 7 | 0.408547 | 0.410582 | 0.412138 | 0.416559 | 0.14659 | 0.160736 | 0.179541 | 0.174418 | 0.763025 | 0.764506 | 0.77739 | 0.78056 |
| Over_dim 256 10_Targets | Over_dim 128 10_Targets | Over_dim 64 10_Targets | Over_dim 32 10_Targets | Over_dim 256 Mnist | Over_dim 128 Mnist | Over_dim 64 Mnist | Over_dim 32 Mnist | Over_dim 256 Noisy | Over_dim 128 Noisy | Over_dim 64 Noisy | Over_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.266176 | 0.266259 | 0.266265 | 0.266287 | 0.0420023 | 0.0501929 | 0.0512275 | 0.0514505 | 0.377219 | 0.377765 | 0.381 | 0.383893 |
| 1 | 0.2667 | 0.266844 | 0.267105 | 0.266927 | 0.0534012 | 0.0619753 | 0.0653142 | 0.0649658 | 0.388644 | 0.389371 | 0.394176 | 0.398215 |
| 2 | 0.266752 | 0.266928 | 0.267185 | 0.26706 | 0.0659112 | 0.0752022 | 0.0804506 | 0.0792816 | 0.399575 | 0.400466 | 0.406336 | 0.410968 |
| 3 | 0.266754 | 0.266927 | 0.267192 | 0.267068 | 0.0785438 | 0.0884157 | 0.0951607 | 0.0931112 | 0.409904 | 0.410682 | 0.417268 | 0.422209 |
| 4 | 0.266754 | 0.266927 | 0.267192 | 0.26707 | 0.0909992 | 0.101313 | 0.109139 | 0.106226 | 0.419553 | 0.419966 | 0.426995 | 0.432025 |
| 5 | 0.266754 | 0.266927 | 0.267192 | 0.26707 | 0.103161 | 0.113601 | 0.122301 | 0.119009 | 0.428517 | 0.428375 | 0.435653 | 0.440641 |
| 6 | 0.266754 | 0.266927 | 0.267192 | 0.26707 | 0.115011 | 0.125307 | 0.134541 | 0.130886 | 0.436812 | 0.43601 | 0.443449 | 0.448217 |
| 7 | 0.266754 | 0.266927 | 0.267192 | 0.26707 | 0.126549 | 0.136452 | 0.145924 | 0.142137 | 0.44447 | 0.442959 | 0.450576 | 0.454876 |
predictions_df_10
| Over_dim 256 10_Targets | Over_dim 128 10_Targets | Over_dim 64 10_Targets | Over_dim 32 10_Targets | Over_dim 256 Mnist | Over_dim 128 Mnist | Over_dim 64 Mnist | Over_dim 32 Mnist | Over_dim 256 Noisy | Over_dim 128 Noisy | Over_dim 64 Noisy | Over_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.9805 | 0.9781 | 0.9772 | 0.9713 | 0.9659 | 0.9702 | 0.9711 | 0.9697 | 0.9665 | 0.9662 | 0.9661 | 0.9638 |
| 1 | 0.9766 | 0.9776 | 0.9761 | 0.9691 | 0.9662 | 0.9681 | 0.9687 | 0.9664 | 0.9577 | 0.9562 | 0.9527 | 0.9454 |
| 2 | 0.9762 | 0.9775 | 0.9759 | 0.9688 | 0.9579 | 0.9553 | 0.957 | 0.9515 | 0.9418 | 0.9394 | 0.9274 | 0.9155 |
| 3 | 0.9762 | 0.9775 | 0.9759 | 0.9687 | 0.9422 | 0.9383 | 0.9361 | 0.9324 | 0.9202 | 0.9201 | 0.8991 | 0.8837 |
| 4 | 0.9762 | 0.9775 | 0.9759 | 0.9687 | 0.9196 | 0.917 | 0.9053 | 0.9105 | 0.8994 | 0.898 | 0.8684 | 0.8491 |
| 5 | 0.9762 | 0.9775 | 0.9759 | 0.9687 | 0.8913 | 0.8922 | 0.8722 | 0.8832 | 0.8748 | 0.8737 | 0.8387 | 0.8124 |
| 6 | 0.9762 | 0.9775 | 0.9759 | 0.9687 | 0.8585 | 0.859 | 0.8349 | 0.8542 | 0.8501 | 0.8472 | 0.8101 | 0.7747 |
| 7 | 0.9762 | 0.9775 | 0.9759 | 0.9687 | 0.82 | 0.8287 | 0.7946 | 0.8205 | 0.8261 | 0.8173 | 0.7832 | 0.7406 |
| Over_dim 256 10_Targets | Over_dim 128 10_Targets | Over_dim 64 10_Targets | Over_dim 32 10_Targets | Over_dim 256 Mnist | Over_dim 128 Mnist | Over_dim 64 Mnist | Over_dim 32 Mnist | Over_dim 256 Noisy | Over_dim 128 Noisy | Over_dim 64 Noisy | Over_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.405328 | 0.406613 | 0.407167 | 0.410978 | 0.0333458 | 0.0389269 | 0.0394954 | 0.0410863 | 0.653283 | 0.657485 | 0.659003 | 0.658313 |
| 1 | 0.409092 | 0.410386 | 0.4124 | 0.416181 | 0.0440291 | 0.0515125 | 0.0552519 | 0.0562369 | 0.670243 | 0.674922 | 0.679675 | 0.679591 |
| 2 | 0.409344 | 0.410811 | 0.412739 | 0.416988 | 0.0594835 | 0.0686068 | 0.0757398 | 0.0757018 | 0.687484 | 0.692443 | 0.69998 | 0.700936 |
| 3 | 0.409355 | 0.410837 | 0.412753 | 0.417028 | 0.0774327 | 0.0878542 | 0.0979168 | 0.0965847 | 0.704287 | 0.709185 | 0.718693 | 0.720672 |
| 4 | 0.409355 | 0.410838 | 0.412754 | 0.417044 | 0.0967377 | 0.107612 | 0.120455 | 0.117765 | 0.72042 | 0.724872 | 0.73569 | 0.738388 |
| 5 | 0.409355 | 0.410838 | 0.412754 | 0.417044 | 0.116774 | 0.127634 | 0.142659 | 0.138862 | 0.73572 | 0.739455 | 0.751056 | 0.754168 |
| 6 | 0.409355 | 0.410838 | 0.412754 | 0.417045 | 0.137056 | 0.147459 | 0.163975 | 0.160157 | 0.750106 | 0.752948 | 0.764999 | 0.768233 |
| 7 | 0.409355 | 0.410838 | 0.412754 | 0.417045 | 0.157369 | 0.167234 | 0.18434 | 0.183046 | 0.763543 | 0.765385 | 0.777726 | 0.780782 |
| Over_dim 256 10_Targets | Over_dim 128 10_Targets | Over_dim 64 10_Targets | Over_dim 32 10_Targets | Over_dim 256 Mnist | Over_dim 128 Mnist | Over_dim 64 Mnist | Over_dim 32 Mnist | Over_dim 256 Noisy | Over_dim 128 Noisy | Over_dim 64 Noisy | Over_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.266363 | 0.266278 | 0.266339 | 0.266338 | 0.0556677 | 0.0598691 | 0.0604611 | 0.0613728 | 0.379662 | 0.379864 | 0.382904 | 0.385727 |
| 1 | 0.267164 | 0.266974 | 0.267449 | 0.267172 | 0.0632183 | 0.0689381 | 0.0717502 | 0.0719355 | 0.389717 | 0.390358 | 0.395072 | 0.39906 |
| 2 | 0.267217 | 0.267066 | 0.267526 | 0.267314 | 0.0740883 | 0.0807967 | 0.0855434 | 0.0848927 | 0.400247 | 0.401095 | 0.406935 | 0.411506 |
| 3 | 0.267218 | 0.267072 | 0.267529 | 0.267326 | 0.0858968 | 0.0933337 | 0.0994873 | 0.0980099 | 0.410373 | 0.411149 | 0.417695 | 0.422615 |
| 4 | 0.267219 | 0.267072 | 0.26753 | 0.267329 | 0.0978699 | 0.105624 | 0.11294 | 0.110678 | 0.419902 | 0.420359 | 0.427314 | 0.43236 |
| 5 | 0.267219 | 0.267072 | 0.26753 | 0.267329 | 0.109744 | 0.117582 | 0.125656 | 0.122814 | 0.428788 | 0.428758 | 0.435909 | 0.440893 |
| 6 | 0.267219 | 0.267072 | 0.26753 | 0.267329 | 0.121364 | 0.129068 | 0.137524 | 0.134672 | 0.437029 | 0.436406 | 0.443647 | 0.448393 |
| 7 | 0.267219 | 0.267072 | 0.26753 | 0.267329 | 0.13268 | 0.140225 | 0.14863 | 0.147019 | 0.444639 | 0.443368 | 0.450685 | 0.454998 |
predictions_df_20
| Over_dim 256 10_Targets | Over_dim 128 10_Targets | Over_dim 64 10_Targets | Over_dim 32 10_Targets | Over_dim 256 Mnist | Over_dim 128 Mnist | Over_dim 64 Mnist | Over_dim 32 Mnist | Over_dim 256 Noisy | Over_dim 128 Noisy | Over_dim 64 Noisy | Over_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.9693 | 0.9714 | 0.9702 | 0.9612 | 0.9441 | 0.9522 | 0.9544 | 0.9553 | 0.9612 | 0.9622 | 0.9601 | 0.9581 |
| 1 | 0.9651 | 0.9706 | 0.9679 | 0.9584 | 0.9499 | 0.9551 | 0.957 | 0.9542 | 0.9526 | 0.9525 | 0.9464 | 0.9412 |
| 2 | 0.9648 | 0.9706 | 0.9675 | 0.958 | 0.9363 | 0.9406 | 0.9425 | 0.9406 | 0.9372 | 0.935 | 0.9236 | 0.914 |
| 3 | 0.9647 | 0.9706 | 0.9675 | 0.958 | 0.9129 | 0.9234 | 0.9184 | 0.9201 | 0.9156 | 0.9173 | 0.8967 | 0.8827 |
| 4 | 0.9647 | 0.9706 | 0.9675 | 0.958 | 0.888 | 0.8999 | 0.8883 | 0.8907 | 0.8952 | 0.8917 | 0.868 | 0.8479 |
| 5 | 0.9647 | 0.9706 | 0.9675 | 0.958 | 0.8555 | 0.8721 | 0.8515 | 0.8561 | 0.8723 | 0.8672 | 0.8376 | 0.8133 |
| 6 | 0.9647 | 0.9706 | 0.9675 | 0.958 | 0.8176 | 0.843 | 0.81 | 0.8258 | 0.8462 | 0.8444 | 0.8119 | 0.7737 |
| 7 | 0.9647 | 0.9706 | 0.9675 | 0.958 | 0.7796 | 0.8158 | 0.7655 | 0.793 | 0.8211 | 0.8176 | 0.7843 | 0.7387 |
| Over_dim 256 10_Targets | Over_dim 128 10_Targets | Over_dim 64 10_Targets | Over_dim 32 10_Targets | Over_dim 256 Mnist | Over_dim 128 Mnist | Over_dim 64 Mnist | Over_dim 32 Mnist | Over_dim 256 Noisy | Over_dim 128 Noisy | Over_dim 64 Noisy | Over_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.404812 | 0.405826 | 0.405897 | 0.409101 | 0.0476364 | 0.0508992 | 0.0513891 | 0.054874 | 0.655091 | 0.659466 | 0.660997 | 0.660077 |
| 1 | 0.410544 | 0.410936 | 0.413225 | 0.416117 | 0.0573917 | 0.0622637 | 0.0658907 | 0.0687528 | 0.671973 | 0.676681 | 0.681345 | 0.681223 |
| 2 | 0.411045 | 0.411507 | 0.41384 | 0.41714 | 0.0728086 | 0.0786207 | 0.0856832 | 0.0875705 | 0.688937 | 0.693977 | 0.701362 | 0.702559 |
| 3 | 0.411084 | 0.411561 | 0.413878 | 0.417211 | 0.0909776 | 0.0971089 | 0.107479 | 0.108059 | 0.705485 | 0.710578 | 0.719804 | 0.722123 |
| 4 | 0.411085 | 0.411562 | 0.41388 | 0.417238 | 0.110541 | 0.116423 | 0.129766 | 0.12892 | 0.721363 | 0.726075 | 0.736547 | 0.739582 |
| 5 | 0.411085 | 0.411562 | 0.41388 | 0.417247 | 0.130753 | 0.135976 | 0.151622 | 0.149689 | 0.736414 | 0.740388 | 0.751713 | 0.755095 |
| 6 | 0.411085 | 0.411562 | 0.41388 | 0.417248 | 0.151134 | 0.155557 | 0.172648 | 0.171133 | 0.750558 | 0.753595 | 0.765554 | 0.768925 |
| 7 | 0.411085 | 0.411562 | 0.41388 | 0.417248 | 0.171505 | 0.176008 | 0.193032 | 0.192191 | 0.763808 | 0.765819 | 0.77827 | 0.781337 |
| Over_dim 256 10_Targets | Over_dim 128 10_Targets | Over_dim 64 10_Targets | Over_dim 32 10_Targets | Over_dim 256 Mnist | Over_dim 128 Mnist | Over_dim 64 Mnist | Over_dim 32 Mnist | Over_dim 256 Noisy | Over_dim 128 Noisy | Over_dim 64 Noisy | Over_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.266922 | 0.26649 | 0.266489 | 0.266256 | 0.0682348 | 0.0698025 | 0.0704383 | 0.0725424 | 0.382478 | 0.382324 | 0.385182 | 0.38791 |
| 1 | 0.268074 | 0.267347 | 0.267999 | 0.267275 | 0.0736629 | 0.0769926 | 0.0796895 | 0.0811094 | 0.391087 | 0.391645 | 0.396249 | 0.400277 |
| 2 | 0.268185 | 0.267467 | 0.268133 | 0.267427 | 0.0834695 | 0.0877248 | 0.0923053 | 0.0929217 | 0.401138 | 0.402035 | 0.407707 | 0.412436 |
| 3 | 0.268192 | 0.26747 | 0.268142 | 0.267443 | 0.0947285 | 0.0993894 | 0.105575 | 0.105339 | 0.410991 | 0.411914 | 0.418236 | 0.423357 |
| 4 | 0.268192 | 0.267469 | 0.268143 | 0.267448 | 0.106408 | 0.111121 | 0.118582 | 0.117514 | 0.420326 | 0.420975 | 0.427698 | 0.432942 |
| 5 | 0.268192 | 0.267469 | 0.268143 | 0.267449 | 0.118077 | 0.122631 | 0.130924 | 0.129264 | 0.429066 | 0.429223 | 0.43619 | 0.44134 |
| 6 | 0.268192 | 0.267469 | 0.268143 | 0.267449 | 0.129521 | 0.133831 | 0.142503 | 0.141032 | 0.437181 | 0.436723 | 0.443874 | 0.448714 |
| 7 | 0.268192 | 0.267469 | 0.268143 | 0.267449 | 0.140728 | 0.145158 | 0.153511 | 0.152358 | 0.444698 | 0.443568 | 0.450883 | 0.455246 |
predictions_df_30
| Over_dim 256 10_Targets | Over_dim 128 10_Targets | Over_dim 64 10_Targets | Over_dim 32 10_Targets | Over_dim 256 Mnist | Over_dim 128 Mnist | Over_dim 64 Mnist | Over_dim 32 Mnist | Over_dim 256 Noisy | Over_dim 128 Noisy | Over_dim 64 Noisy | Over_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.9517 | 0.9586 | 0.9573 | 0.9488 | 0.9179 | 0.9259 | 0.934 | 0.9285 | 0.9536 | 0.9542 | 0.952 | 0.9501 |
| 1 | 0.9447 | 0.9589 | 0.9531 | 0.9472 | 0.925 | 0.9303 | 0.9387 | 0.9306 | 0.949 | 0.9444 | 0.9407 | 0.9345 |
| 2 | 0.9441 | 0.9587 | 0.9527 | 0.9471 | 0.9093 | 0.9182 | 0.9203 | 0.9108 | 0.9305 | 0.9265 | 0.9161 | 0.9069 |
| 3 | 0.9442 | 0.9586 | 0.9527 | 0.947 | 0.8811 | 0.896 | 0.8882 | 0.8874 | 0.9112 | 0.9056 | 0.89 | 0.8779 |
| 4 | 0.9442 | 0.9586 | 0.9527 | 0.947 | 0.8496 | 0.8691 | 0.8524 | 0.8577 | 0.8886 | 0.8852 | 0.8631 | 0.8421 |
| 5 | 0.9442 | 0.9586 | 0.9527 | 0.947 | 0.8114 | 0.8385 | 0.8115 | 0.8227 | 0.8644 | 0.861 | 0.8353 | 0.8076 |
| 6 | 0.9442 | 0.9586 | 0.9527 | 0.947 | 0.7656 | 0.8047 | 0.774 | 0.7875 | 0.8387 | 0.8375 | 0.808 | 0.7703 |
| 7 | 0.9442 | 0.9586 | 0.9527 | 0.947 | 0.7231 | 0.7759 | 0.7319 | 0.7575 | 0.8146 | 0.8097 | 0.781 | 0.7311 |
| Over_dim 256 10_Targets | Over_dim 128 10_Targets | Over_dim 64 10_Targets | Over_dim 32 10_Targets | Over_dim 256 Mnist | Over_dim 128 Mnist | Over_dim 64 Mnist | Over_dim 32 Mnist | Over_dim 256 Noisy | Over_dim 128 Noisy | Over_dim 64 Noisy | Over_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.405582 | 0.405659 | 0.40583 | 0.408721 | 0.0637877 | 0.0646255 | 0.0657407 | 0.0765114 | 0.657328 | 0.661879 | 0.663047 | 0.661962 |
| 1 | 0.414465 | 0.412777 | 0.415919 | 0.417874 | 0.0731841 | 0.0750521 | 0.0793314 | 0.0898674 | 0.674164 | 0.679018 | 0.68305 | 0.682785 |
| 2 | 0.415131 | 0.413465 | 0.416779 | 0.419075 | 0.0887943 | 0.0907445 | 0.0984559 | 0.107928 | 0.690811 | 0.696008 | 0.702796 | 0.703853 |
| 3 | 0.41518 | 0.413526 | 0.416841 | 0.419167 | 0.107233 | 0.10866 | 0.119593 | 0.127873 | 0.707128 | 0.712274 | 0.721087 | 0.723315 |
| 4 | 0.415181 | 0.413539 | 0.416843 | 0.419187 | 0.126994 | 0.127409 | 0.141191 | 0.148316 | 0.722884 | 0.727532 | 0.737742 | 0.740855 |
| 5 | 0.415181 | 0.41354 | 0.416843 | 0.419187 | 0.147347 | 0.146291 | 0.162449 | 0.16919 | 0.737835 | 0.741718 | 0.752881 | 0.756435 |
| 6 | 0.415181 | 0.41354 | 0.416843 | 0.419188 | 0.167816 | 0.165003 | 0.183159 | 0.189917 | 0.75184 | 0.754881 | 0.766631 | 0.770237 |
| 7 | 0.415181 | 0.41354 | 0.416843 | 0.419188 | 0.188315 | 0.18339 | 0.202814 | 0.211439 | 0.764875 | 0.767038 | 0.779143 | 0.782515 |
| Over_dim 256 10_Targets | Over_dim 128 10_Targets | Over_dim 64 10_Targets | Over_dim 32 10_Targets | Over_dim 256 Mnist | Over_dim 128 Mnist | Over_dim 64 Mnist | Over_dim 32 Mnist | Over_dim 256 Noisy | Over_dim 128 Noisy | Over_dim 64 Noisy | Over_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.268456 | 0.267225 | 0.267471 | 0.267066 | 0.0810928 | 0.0804933 | 0.0814174 | 0.0875742 | 0.38575 | 0.385292 | 0.387725 | 0.390414 |
| 1 | 0.270349 | 0.268412 | 0.26955 | 0.268317 | 0.0851522 | 0.0862122 | 0.0890692 | 0.0946603 | 0.392776 | 0.393402 | 0.397597 | 0.401546 |
| 2 | 0.270487 | 0.268532 | 0.269743 | 0.268509 | 0.0942112 | 0.0958726 | 0.100568 | 0.105317 | 0.402278 | 0.403322 | 0.40861 | 0.413294 |
| 3 | 0.270498 | 0.268546 | 0.269755 | 0.268528 | 0.104979 | 0.106771 | 0.112979 | 0.116932 | 0.411866 | 0.41291 | 0.418926 | 0.424071 |
| 4 | 0.270499 | 0.268546 | 0.269756 | 0.268531 | 0.116304 | 0.11788 | 0.125308 | 0.128573 | 0.421056 | 0.421777 | 0.428266 | 0.433625 |
| 5 | 0.270499 | 0.268547 | 0.269756 | 0.268531 | 0.127693 | 0.128793 | 0.137139 | 0.140143 | 0.429678 | 0.429908 | 0.436675 | 0.442 |
| 6 | 0.270499 | 0.268547 | 0.269756 | 0.268531 | 0.138922 | 0.139359 | 0.148423 | 0.151385 | 0.437678 | 0.437343 | 0.444268 | 0.44934 |
| 7 | 0.270499 | 0.268547 | 0.269756 | 0.268531 | 0.149971 | 0.149541 | 0.158957 | 0.162761 | 0.445068 | 0.444137 | 0.451151 | 0.4558 |
predictions_df_40
| Over_dim 256 10_Targets | Over_dim 128 10_Targets | Over_dim 64 10_Targets | Over_dim 32 10_Targets | Over_dim 256 Mnist | Over_dim 128 Mnist | Over_dim 64 Mnist | Over_dim 32 Mnist | Over_dim 256 Noisy | Over_dim 128 Noisy | Over_dim 64 Noisy | Over_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.9247 | 0.9364 | 0.9309 | 0.9244 | 0.8815 | 0.8905 | 0.9012 | 0.892 | 0.944 | 0.9457 | 0.9398 | 0.9431 |
| 1 | 0.9117 | 0.9344 | 0.9219 | 0.9239 | 0.89 | 0.8964 | 0.9062 | 0.8951 | 0.9377 | 0.9363 | 0.9286 | 0.9253 |
| 2 | 0.9114 | 0.9342 | 0.9211 | 0.9238 | 0.8736 | 0.881 | 0.8892 | 0.8775 | 0.9202 | 0.9203 | 0.9071 | 0.8989 |
| 3 | 0.9114 | 0.9341 | 0.9211 | 0.9238 | 0.8435 | 0.8592 | 0.8559 | 0.8527 | 0.8985 | 0.902 | 0.88 | 0.8678 |
| 4 | 0.9114 | 0.9341 | 0.9211 | 0.9238 | 0.8089 | 0.8272 | 0.8178 | 0.8179 | 0.8748 | 0.8815 | 0.8505 | 0.8334 |
| 5 | 0.9114 | 0.9341 | 0.9211 | 0.9238 | 0.7656 | 0.7998 | 0.7767 | 0.7834 | 0.8532 | 0.8592 | 0.8246 | 0.8002 |
| 6 | 0.9114 | 0.9341 | 0.9211 | 0.9238 | 0.7261 | 0.7687 | 0.7332 | 0.7535 | 0.8281 | 0.8336 | 0.7968 | 0.7647 |
| 7 | 0.9114 | 0.9341 | 0.9211 | 0.9238 | 0.686 | 0.7401 | 0.6899 | 0.7201 | 0.8062 | 0.8043 | 0.7696 | 0.73 |
| Over_dim 256 10_Targets | Over_dim 128 10_Targets | Over_dim 64 10_Targets | Over_dim 32 10_Targets | Over_dim 256 Mnist | Over_dim 128 Mnist | Over_dim 64 Mnist | Over_dim 32 Mnist | Over_dim 256 Noisy | Over_dim 128 Noisy | Over_dim 64 Noisy | Over_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.408918 | 0.404708 | 0.406346 | 0.408498 | 0.0815687 | 0.0811727 | 0.0827611 | 0.107204 | 0.660047 | 0.665153 | 0.66597 | 0.66461 |
| 1 | 0.421742 | 0.415538 | 0.421957 | 0.42133 | 0.0907393 | 0.090921 | 0.0959053 | 0.119559 | 0.677094 | 0.682366 | 0.6859 | 0.685171 |
| 2 | 0.422454 | 0.417246 | 0.423561 | 0.423075 | 0.106424 | 0.106106 | 0.114538 | 0.136958 | 0.69355 | 0.699084 | 0.705464 | 0.706029 |
| 3 | 0.42247 | 0.417425 | 0.42371 | 0.423242 | 0.12501 | 0.123592 | 0.13508 | 0.156386 | 0.709577 | 0.714983 | 0.723496 | 0.725163 |
| 4 | 0.42247 | 0.417485 | 0.423718 | 0.42327 | 0.144778 | 0.141914 | 0.155978 | 0.176311 | 0.725006 | 0.729903 | 0.739906 | 0.74229 |
| 5 | 0.42247 | 0.417486 | 0.423718 | 0.423272 | 0.164949 | 0.160408 | 0.176485 | 0.196351 | 0.739677 | 0.743752 | 0.75481 | 0.757575 |
| 6 | 0.42247 | 0.417486 | 0.423718 | 0.423272 | 0.185036 | 0.178806 | 0.196173 | 0.216743 | 0.753508 | 0.756592 | 0.768401 | 0.771161 |
| 7 | 0.42247 | 0.417486 | 0.423718 | 0.423272 | 0.20501 | 0.197013 | 0.214983 | 0.237287 | 0.766461 | 0.768522 | 0.780834 | 0.78317 |
| Over_dim 256 10_Targets | Over_dim 128 10_Targets | Over_dim 64 10_Targets | Over_dim 32 10_Targets | Over_dim 256 Mnist | Over_dim 128 Mnist | Over_dim 64 Mnist | Over_dim 32 Mnist | Over_dim 256 Noisy | Over_dim 128 Noisy | Over_dim 64 Noisy | Over_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.27165 | 0.268348 | 0.269891 | 0.268503 | 0.0942749 | 0.0924013 | 0.0938089 | 0.107067 | 0.389715 | 0.38899 | 0.391144 | 0.393661 |
| 1 | 0.274481 | 0.270355 | 0.27315 | 0.270445 | 0.0973057 | 0.0970429 | 0.100312 | 0.112816 | 0.395084 | 0.395793 | 0.399744 | 0.403409 |
| 2 | 0.274624 | 0.270698 | 0.273514 | 0.270744 | 0.105656 | 0.10585 | 0.110867 | 0.122433 | 0.403987 | 0.405185 | 0.410273 | 0.414638 |
| 3 | 0.274626 | 0.27073 | 0.273547 | 0.270782 | 0.11596 | 0.116091 | 0.122483 | 0.133257 | 0.413223 | 0.41444 | 0.420292 | 0.425084 |
| 4 | 0.274626 | 0.270746 | 0.273549 | 0.270787 | 0.126863 | 0.12669 | 0.134097 | 0.144222 | 0.422142 | 0.423081 | 0.429415 | 0.434357 |
| 5 | 0.274626 | 0.270747 | 0.273549 | 0.270788 | 0.137855 | 0.137215 | 0.145289 | 0.155061 | 0.430568 | 0.431012 | 0.437669 | 0.442528 |
| 6 | 0.274626 | 0.270747 | 0.273549 | 0.270788 | 0.148694 | 0.147489 | 0.155885 | 0.165902 | 0.438448 | 0.43829 | 0.445167 | 0.449715 |
| 7 | 0.274626 | 0.270747 | 0.273549 | 0.270788 | 0.159342 | 0.157458 | 0.16586 | 0.176662 | 0.445777 | 0.444982 | 0.452014 | 0.456018 |
predictions_df_50
| Over_dim 256 10_Targets | Over_dim 128 10_Targets | Over_dim 64 10_Targets | Over_dim 32 10_Targets | Over_dim 256 Mnist | Over_dim 128 Mnist | Over_dim 64 Mnist | Over_dim 32 Mnist | Over_dim 256 Noisy | Over_dim 128 Noisy | Over_dim 64 Noisy | Over_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.8851 | 0.9044 | 0.8963 | 0.8952 | 0.8355 | 0.849 | 0.8594 | 0.8407 | 0.9295 | 0.9318 | 0.9294 | 0.9269 |
| 1 | 0.868 | 0.9011 | 0.8869 | 0.8963 | 0.8443 | 0.8513 | 0.8655 | 0.8473 | 0.9254 | 0.9259 | 0.9187 | 0.9124 |
| 2 | 0.8668 | 0.9004 | 0.8866 | 0.8964 | 0.8288 | 0.8342 | 0.847 | 0.8309 | 0.9067 | 0.9084 | 0.8946 | 0.8855 |
| 3 | 0.8668 | 0.9005 | 0.8865 | 0.8965 | 0.7917 | 0.8144 | 0.808 | 0.8014 | 0.8863 | 0.8854 | 0.8684 | 0.8563 |
| 4 | 0.8668 | 0.9005 | 0.8865 | 0.8965 | 0.7554 | 0.7838 | 0.7631 | 0.7679 | 0.8631 | 0.8654 | 0.8416 | 0.8242 |
| 5 | 0.8668 | 0.9005 | 0.8865 | 0.8965 | 0.7144 | 0.7555 | 0.7223 | 0.7324 | 0.8426 | 0.841 | 0.814 | 0.7919 |
| 6 | 0.8668 | 0.9005 | 0.8865 | 0.8965 | 0.6666 | 0.7238 | 0.6812 | 0.6985 | 0.8222 | 0.8157 | 0.7901 | 0.7564 |
| 7 | 0.8668 | 0.9005 | 0.8865 | 0.8965 | 0.6234 | 0.6877 | 0.6415 | 0.6657 | 0.7998 | 0.79 | 0.7663 | 0.724 |
| Over_dim 256 10_Targets | Over_dim 128 10_Targets | Over_dim 64 10_Targets | Over_dim 32 10_Targets | Over_dim 256 Mnist | Over_dim 128 Mnist | Over_dim 64 Mnist | Over_dim 32 Mnist | Over_dim 256 Noisy | Over_dim 128 Noisy | Over_dim 64 Noisy | Over_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.412852 | 0.406614 | 0.408193 | 0.409169 | 0.101264 | 0.0998812 | 0.103731 | 0.162213 | 0.663794 | 0.66902 | 0.669493 | 0.66782 |
| 1 | 0.430994 | 0.422234 | 0.429382 | 0.425458 | 0.11054 | 0.1092 | 0.116311 | 0.174101 | 0.680951 | 0.6863 | 0.689281 | 0.688349 |
| 2 | 0.432234 | 0.424348 | 0.431383 | 0.427456 | 0.126387 | 0.12373 | 0.134266 | 0.190654 | 0.697075 | 0.702831 | 0.708535 | 0.708994 |
| 3 | 0.432353 | 0.42457 | 0.431596 | 0.427622 | 0.14496 | 0.140531 | 0.15411 | 0.209184 | 0.712687 | 0.718585 | 0.726254 | 0.727799 |
| 4 | 0.43236 | 0.424627 | 0.431611 | 0.427647 | 0.16459 | 0.158335 | 0.174311 | 0.228159 | 0.727693 | 0.733294 | 0.742473 | 0.744692 |
| 5 | 0.43236 | 0.424628 | 0.431612 | 0.427649 | 0.184729 | 0.176416 | 0.194056 | 0.247575 | 0.74194 | 0.746969 | 0.757216 | 0.759728 |
| 6 | 0.43236 | 0.424628 | 0.431612 | 0.42765 | 0.20462 | 0.194417 | 0.213132 | 0.267317 | 0.755357 | 0.759683 | 0.770581 | 0.773133 |
| 7 | 0.43236 | 0.424628 | 0.431612 | 0.42765 | 0.223933 | 0.211721 | 0.231085 | 0.287314 | 0.767911 | 0.771502 | 0.78273 | 0.785083 |
| Over_dim 256 10_Targets | Over_dim 128 10_Targets | Over_dim 64 10_Targets | Over_dim 32 10_Targets | Over_dim 256 Mnist | Over_dim 128 Mnist | Over_dim 64 Mnist | Over_dim 32 Mnist | Over_dim 256 Noisy | Over_dim 128 Noisy | Over_dim 64 Noisy | Over_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.275632 | 0.27107 | 0.273039 | 0.270521 | 0.107996 | 0.105262 | 0.107844 | 0.138404 | 0.39426 | 0.393183 | 0.394988 | 0.397422 |
| 1 | 0.279761 | 0.27413 | 0.277347 | 0.272787 | 0.110444 | 0.109095 | 0.113331 | 0.143218 | 0.397946 | 0.39865 | 0.402199 | 0.405826 |
| 2 | 0.280041 | 0.274569 | 0.2778 | 0.273087 | 0.118278 | 0.117014 | 0.122926 | 0.151781 | 0.406126 | 0.407545 | 0.412128 | 0.416495 |
| 3 | 0.280074 | 0.274602 | 0.277864 | 0.27312 | 0.128083 | 0.126471 | 0.133759 | 0.161687 | 0.414922 | 0.416541 | 0.421827 | 0.426594 |
| 4 | 0.280074 | 0.274616 | 0.277867 | 0.273124 | 0.138537 | 0.136461 | 0.144689 | 0.171816 | 0.423509 | 0.42498 | 0.430772 | 0.43565 |
| 5 | 0.280074 | 0.274616 | 0.277868 | 0.273125 | 0.149209 | 0.146492 | 0.155257 | 0.18206 | 0.431657 | 0.432776 | 0.438898 | 0.443642 |
| 6 | 0.280074 | 0.274616 | 0.277868 | 0.273125 | 0.159672 | 0.15638 | 0.165324 | 0.192342 | 0.439288 | 0.439938 | 0.446279 | 0.450684 |
| 7 | 0.280074 | 0.274616 | 0.277868 | 0.273125 | 0.16978 | 0.165788 | 0.17471 | 0.202618 | 0.446383 | 0.446515 | 0.452983 | 0.456901 |
predictions_df_60
| Over_dim 256 10_Targets | Over_dim 128 10_Targets | Over_dim 64 10_Targets | Over_dim 32 10_Targets | Over_dim 256 Mnist | Over_dim 128 Mnist | Over_dim 64 Mnist | Over_dim 32 Mnist | Over_dim 256 Noisy | Over_dim 128 Noisy | Over_dim 64 Noisy | Over_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.8293 | 0.8513 | 0.8416 | 0.8467 | 0.7781 | 0.7877 | 0.8027 | 0.783 | 0.9045 | 0.9085 | 0.904 | 0.9008 |
| 1 | 0.8076 | 0.85 | 0.8315 | 0.8478 | 0.7917 | 0.7932 | 0.8079 | 0.7866 | 0.9057 | 0.9058 | 0.8982 | 0.8878 |
| 2 | 0.8047 | 0.8497 | 0.831 | 0.8474 | 0.7655 | 0.7759 | 0.783 | 0.7648 | 0.8869 | 0.89 | 0.8744 | 0.8651 |
| 3 | 0.8046 | 0.8499 | 0.831 | 0.8473 | 0.7344 | 0.7546 | 0.7439 | 0.7365 | 0.8627 | 0.8673 | 0.8477 | 0.8326 |
| 4 | 0.8046 | 0.8499 | 0.831 | 0.8473 | 0.6926 | 0.7245 | 0.7032 | 0.705 | 0.8393 | 0.8481 | 0.8223 | 0.8008 |
| 5 | 0.8046 | 0.8499 | 0.831 | 0.8473 | 0.6509 | 0.6924 | 0.6592 | 0.6736 | 0.8196 | 0.8257 | 0.8011 | 0.7652 |
| 6 | 0.8046 | 0.8499 | 0.831 | 0.8473 | 0.613 | 0.6652 | 0.6198 | 0.6457 | 0.7989 | 0.8024 | 0.7745 | 0.7327 |
| 7 | 0.8046 | 0.8499 | 0.831 | 0.8473 | 0.573 | 0.6335 | 0.5817 | 0.6125 | 0.7762 | 0.7756 | 0.7499 | 0.6993 |
| Over_dim 256 10_Targets | Over_dim 128 10_Targets | Over_dim 64 10_Targets | Over_dim 32 10_Targets | Over_dim 256 Mnist | Over_dim 128 Mnist | Over_dim 64 Mnist | Over_dim 32 Mnist | Over_dim 256 Noisy | Over_dim 128 Noisy | Over_dim 64 Noisy | Over_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.419886 | 0.411294 | 0.412447 | 0.411952 | 0.124999 | 0.123663 | 0.131314 | 0.235707 | 0.668549 | 0.673888 | 0.674354 | 0.672273 |
| 1 | 0.444337 | 0.43164 | 0.441538 | 0.433257 | 0.134295 | 0.13283 | 0.143845 | 0.247752 | 0.686277 | 0.691478 | 0.694254 | 0.692859 |
| 2 | 0.446303 | 0.434637 | 0.444467 | 0.436029 | 0.150105 | 0.146812 | 0.161394 | 0.263452 | 0.702383 | 0.707702 | 0.713304 | 0.713358 |
| 3 | 0.446349 | 0.434948 | 0.444626 | 0.436359 | 0.168539 | 0.162892 | 0.18058 | 0.280779 | 0.717768 | 0.723062 | 0.730698 | 0.731896 |
| 4 | 0.446351 | 0.435003 | 0.444634 | 0.436413 | 0.187944 | 0.179856 | 0.199873 | 0.299119 | 0.732477 | 0.737455 | 0.746531 | 0.748442 |
| 5 | 0.446351 | 0.435004 | 0.444634 | 0.436441 | 0.207416 | 0.197261 | 0.218896 | 0.316973 | 0.746344 | 0.750844 | 0.760853 | 0.763126 |
| 6 | 0.446351 | 0.435004 | 0.444634 | 0.436442 | 0.226858 | 0.214797 | 0.236993 | 0.33414 | 0.759442 | 0.763268 | 0.773779 | 0.776236 |
| 7 | 0.446351 | 0.435004 | 0.444634 | 0.436442 | 0.246048 | 0.231771 | 0.25399 | 0.351851 | 0.771752 | 0.77473 | 0.785527 | 0.78796 |
| Over_dim 256 10_Targets | Over_dim 128 10_Targets | Over_dim 64 10_Targets | Over_dim 32 10_Targets | Over_dim 256 Mnist | Over_dim 128 Mnist | Over_dim 64 Mnist | Over_dim 32 Mnist | Over_dim 256 Noisy | Over_dim 128 Noisy | Over_dim 64 Noisy | Over_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.281561 | 0.275539 | 0.278318 | 0.274337 | 0.123693 | 0.120816 | 0.125259 | 0.178776 | 0.39998 | 0.398412 | 0.400164 | 0.40243 |
| 1 | 0.287378 | 0.279609 | 0.284309 | 0.277449 | 0.125494 | 0.124055 | 0.130152 | 0.18309 | 0.401991 | 0.402441 | 0.405993 | 0.409265 |
| 2 | 0.287863 | 0.280243 | 0.284936 | 0.277887 | 0.132723 | 0.131234 | 0.139004 | 0.190674 | 0.409495 | 0.410606 | 0.415277 | 0.419267 |
| 3 | 0.28787 | 0.280293 | 0.284972 | 0.277945 | 0.142016 | 0.13997 | 0.149048 | 0.199496 | 0.417881 | 0.419142 | 0.424561 | 0.428998 |
| 4 | 0.28787 | 0.2803 | 0.284974 | 0.277959 | 0.152022 | 0.149257 | 0.159205 | 0.208913 | 0.426154 | 0.427277 | 0.433174 | 0.437773 |
| 5 | 0.28787 | 0.2803 | 0.284974 | 0.277968 | 0.162103 | 0.158705 | 0.169168 | 0.218055 | 0.434008 | 0.434829 | 0.441007 | 0.445534 |
| 6 | 0.28787 | 0.2803 | 0.284974 | 0.277968 | 0.172155 | 0.168097 | 0.178575 | 0.226793 | 0.441393 | 0.441765 | 0.448093 | 0.452397 |
| 7 | 0.28787 | 0.2803 | 0.284974 | 0.277968 | 0.182016 | 0.177111 | 0.187349 | 0.235728 | 0.448304 | 0.44811 | 0.454545 | 0.458469 |
predictions_df_70
| Over_dim 256 10_Targets | Over_dim 128 10_Targets | Over_dim 64 10_Targets | Over_dim 32 10_Targets | Over_dim 256 Mnist | Over_dim 128 Mnist | Over_dim 64 Mnist | Over_dim 32 Mnist | Over_dim 256 Noisy | Over_dim 128 Noisy | Over_dim 64 Noisy | Over_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.76 | 0.7902 | 0.7744 | 0.786 | 0.7126 | 0.7178 | 0.7266 | 0.6939 | 0.8747 | 0.875 | 0.871 | 0.8718 |
| 1 | 0.7382 | 0.7858 | 0.7592 | 0.7873 | 0.7194 | 0.7203 | 0.7309 | 0.7025 | 0.8797 | 0.8777 | 0.8662 | 0.8622 |
| 2 | 0.7366 | 0.784 | 0.7584 | 0.7873 | 0.6917 | 0.7052 | 0.7041 | 0.679 | 0.8616 | 0.8582 | 0.8437 | 0.8336 |
| 3 | 0.7365 | 0.7839 | 0.7584 | 0.7873 | 0.6544 | 0.6811 | 0.6663 | 0.6556 | 0.8394 | 0.8354 | 0.8226 | 0.8035 |
| 4 | 0.7365 | 0.7839 | 0.7584 | 0.7873 | 0.6099 | 0.6536 | 0.6284 | 0.6262 | 0.8197 | 0.8176 | 0.8006 | 0.7752 |
| 5 | 0.7365 | 0.7839 | 0.7584 | 0.7873 | 0.5687 | 0.6246 | 0.5872 | 0.6014 | 0.7989 | 0.7974 | 0.7744 | 0.7436 |
| 6 | 0.7365 | 0.7839 | 0.7584 | 0.7873 | 0.5372 | 0.5988 | 0.551 | 0.573 | 0.7753 | 0.7723 | 0.7486 | 0.7119 |
| 7 | 0.7365 | 0.7839 | 0.7584 | 0.7873 | 0.5019 | 0.5686 | 0.5153 | 0.5444 | 0.7528 | 0.7476 | 0.7266 | 0.679 |
| Over_dim 256 10_Targets | Over_dim 128 10_Targets | Over_dim 64 10_Targets | Over_dim 32 10_Targets | Over_dim 256 Mnist | Over_dim 128 Mnist | Over_dim 64 Mnist | Over_dim 32 Mnist | Over_dim 256 Noisy | Over_dim 128 Noisy | Over_dim 64 Noisy | Over_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.428187 | 0.416046 | 0.418245 | 0.415555 | 0.152239 | 0.150735 | 0.162675 | 0.347507 | 0.675248 | 0.681012 | 0.680903 | 0.677828 |
| 1 | 0.457727 | 0.442886 | 0.456102 | 0.441316 | 0.162095 | 0.160039 | 0.174847 | 0.360955 | 0.693742 | 0.699151 | 0.701008 | 0.698646 |
| 2 | 0.459635 | 0.447228 | 0.459984 | 0.444792 | 0.178231 | 0.173839 | 0.191541 | 0.375518 | 0.709678 | 0.715045 | 0.719694 | 0.718827 |
| 3 | 0.459711 | 0.447789 | 0.460258 | 0.445171 | 0.196378 | 0.189426 | 0.209747 | 0.391719 | 0.724594 | 0.729805 | 0.736586 | 0.736722 |
| 4 | 0.459729 | 0.447848 | 0.460282 | 0.445216 | 0.215238 | 0.20577 | 0.228066 | 0.408664 | 0.738857 | 0.743645 | 0.75186 | 0.752633 |
| 5 | 0.45973 | 0.44785 | 0.460283 | 0.445223 | 0.234203 | 0.222418 | 0.246069 | 0.425644 | 0.752408 | 0.756563 | 0.765646 | 0.766806 |
| 6 | 0.45973 | 0.44785 | 0.460283 | 0.445223 | 0.253419 | 0.238926 | 0.262932 | 0.442558 | 0.765186 | 0.768556 | 0.778119 | 0.77943 |
| 7 | 0.45973 | 0.44785 | 0.460283 | 0.445224 | 0.271975 | 0.255337 | 0.27927 | 0.459808 | 0.777148 | 0.779669 | 0.789503 | 0.790714 |
| Over_dim 256 10_Targets | Over_dim 128 10_Targets | Over_dim 64 10_Targets | Over_dim 32 10_Targets | Over_dim 256 Mnist | Over_dim 128 Mnist | Over_dim 64 Mnist | Over_dim 32 Mnist | Over_dim 256 Noisy | Over_dim 128 Noisy | Over_dim 64 Noisy | Over_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.287936 | 0.280681 | 0.284978 | 0.278411 | 0.140918 | 0.137862 | 0.144484 | 0.238058 | 0.407196 | 0.405316 | 0.406613 | 0.408583 |
| 1 | 0.294739 | 0.286222 | 0.292607 | 0.282081 | 0.142468 | 0.140835 | 0.148596 | 0.242585 | 0.407564 | 0.407877 | 0.410829 | 0.413736 |
| 2 | 0.295188 | 0.287165 | 0.293434 | 0.282684 | 0.149362 | 0.147511 | 0.156464 | 0.249088 | 0.414164 | 0.415225 | 0.419227 | 0.422854 |
| 3 | 0.295208 | 0.287276 | 0.293502 | 0.282754 | 0.158079 | 0.15562 | 0.16558 | 0.256936 | 0.421934 | 0.423169 | 0.427905 | 0.431923 |
| 4 | 0.295212 | 0.287286 | 0.293507 | 0.282762 | 0.167471 | 0.16428 | 0.174903 | 0.265329 | 0.429765 | 0.430863 | 0.436052 | 0.440217 |
| 5 | 0.295212 | 0.287285 | 0.293507 | 0.282764 | 0.177026 | 0.173122 | 0.184068 | 0.273753 | 0.437308 | 0.438065 | 0.443496 | 0.447604 |
| 6 | 0.295212 | 0.287285 | 0.293507 | 0.282764 | 0.18671 | 0.181814 | 0.192648 | 0.282125 | 0.444436 | 0.444719 | 0.450277 | 0.454143 |
| 7 | 0.295212 | 0.287285 | 0.293507 | 0.282764 | 0.196095 | 0.190372 | 0.200943 | 0.290642 | 0.451102 | 0.450854 | 0.456484 | 0.459956 |
predictions_df_80
| Over_dim 256 10_Targets | Over_dim 128 10_Targets | Over_dim 64 10_Targets | Over_dim 32 10_Targets | Over_dim 256 Mnist | Over_dim 128 Mnist | Over_dim 64 Mnist | Over_dim 32 Mnist | Over_dim 256 Noisy | Over_dim 128 Noisy | Over_dim 64 Noisy | Over_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.6746 | 0.7005 | 0.6845 | 0.7026 | 0.6425 | 0.6304 | 0.6454 | 0.5977 | 0.8238 | 0.8209 | 0.8229 | 0.8246 |
| 1 | 0.6494 | 0.6939 | 0.6645 | 0.7068 | 0.6421 | 0.6366 | 0.6488 | 0.6074 | 0.8302 | 0.8311 | 0.8228 | 0.8191 |
| 2 | 0.6484 | 0.693 | 0.6628 | 0.7061 | 0.6157 | 0.6234 | 0.6305 | 0.5872 | 0.8146 | 0.8182 | 0.8061 | 0.7943 |
| 3 | 0.6482 | 0.6928 | 0.6628 | 0.706 | 0.5812 | 0.6012 | 0.5926 | 0.5662 | 0.7925 | 0.7968 | 0.7801 | 0.76 |
| 4 | 0.6482 | 0.6929 | 0.6628 | 0.706 | 0.5479 | 0.5741 | 0.5591 | 0.5409 | 0.7726 | 0.7753 | 0.7548 | 0.7306 |
| 5 | 0.6482 | 0.6929 | 0.6628 | 0.706 | 0.511 | 0.5481 | 0.5209 | 0.5147 | 0.7522 | 0.753 | 0.7321 | 0.7029 |
| 6 | 0.6482 | 0.6929 | 0.6628 | 0.706 | 0.4787 | 0.527 | 0.4877 | 0.4883 | 0.7342 | 0.729 | 0.7063 | 0.6745 |
| 7 | 0.6482 | 0.6929 | 0.6628 | 0.706 | 0.4449 | 0.505 | 0.4569 | 0.4677 | 0.7154 | 0.7057 | 0.6846 | 0.6429 |
| Over_dim 256 10_Targets | Over_dim 128 10_Targets | Over_dim 64 10_Targets | Over_dim 32 10_Targets | Over_dim 256 Mnist | Over_dim 128 Mnist | Over_dim 64 Mnist | Over_dim 32 Mnist | Over_dim 256 Noisy | Over_dim 128 Noisy | Over_dim 64 Noisy | Over_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.438368 | 0.425735 | 0.427351 | 0.426069 | 0.186703 | 0.183769 | 0.201153 | 0.523822 | 0.68479 | 0.690908 | 0.689787 | 0.686328 |
| 1 | 0.474756 | 0.459147 | 0.474367 | 0.458138 | 0.197009 | 0.193261 | 0.213019 | 0.538245 | 0.704542 | 0.710288 | 0.71074 | 0.707977 |
| 2 | 0.477095 | 0.464603 | 0.479313 | 0.46233 | 0.212591 | 0.206633 | 0.228818 | 0.551192 | 0.720647 | 0.726213 | 0.72955 | 0.728422 |
| 3 | 0.477192 | 0.465242 | 0.479642 | 0.462822 | 0.230236 | 0.22166 | 0.245496 | 0.565365 | 0.735193 | 0.740582 | 0.746083 | 0.746135 |
| 4 | 0.477196 | 0.465339 | 0.479667 | 0.462859 | 0.248607 | 0.237122 | 0.262066 | 0.580034 | 0.748897 | 0.75394 | 0.760813 | 0.761637 |
| 5 | 0.477196 | 0.465344 | 0.479669 | 0.462866 | 0.26676 | 0.252732 | 0.278264 | 0.594551 | 0.761817 | 0.766416 | 0.774082 | 0.775365 |
| 6 | 0.477196 | 0.465344 | 0.479669 | 0.462867 | 0.284884 | 0.268356 | 0.293951 | 0.609128 | 0.773955 | 0.777987 | 0.786154 | 0.787546 |
| 7 | 0.477196 | 0.465344 | 0.479669 | 0.462867 | 0.303361 | 0.283716 | 0.308881 | 0.623925 | 0.785315 | 0.78867 | 0.797195 | 0.798359 |
| Over_dim 256 10_Targets | Over_dim 128 10_Targets | Over_dim 64 10_Targets | Over_dim 32 10_Targets | Over_dim 256 Mnist | Over_dim 128 Mnist | Over_dim 64 Mnist | Over_dim 32 Mnist | Over_dim 256 Noisy | Over_dim 128 Noisy | Over_dim 64 Noisy | Over_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.295748 | 0.288371 | 0.293392 | 0.286724 | 0.161564 | 0.157781 | 0.167098 | 0.328476 | 0.416416 | 0.414172 | 0.415 | 0.416771 |
| 1 | 0.304337 | 0.295447 | 0.302875 | 0.291569 | 0.162868 | 0.160531 | 0.170616 | 0.333222 | 0.415303 | 0.415509 | 0.417905 | 0.42039 |
| 2 | 0.304848 | 0.296656 | 0.303962 | 0.292288 | 0.169038 | 0.166686 | 0.177567 | 0.338614 | 0.421042 | 0.422161 | 0.425568 | 0.428821 |
| 3 | 0.304863 | 0.296792 | 0.304037 | 0.292375 | 0.177142 | 0.17424 | 0.185509 | 0.345141 | 0.428114 | 0.42954 | 0.433662 | 0.437403 |
| 4 | 0.304863 | 0.296802 | 0.30404 | 0.292383 | 0.186015 | 0.182195 | 0.19362 | 0.352093 | 0.435347 | 0.436772 | 0.441297 | 0.445255 |
| 5 | 0.304863 | 0.296802 | 0.30404 | 0.292384 | 0.19494 | 0.190266 | 0.201618 | 0.35903 | 0.44238 | 0.443596 | 0.448331 | 0.452268 |
| 6 | 0.304863 | 0.296802 | 0.30404 | 0.292384 | 0.203918 | 0.198345 | 0.209411 | 0.365983 | 0.449044 | 0.449931 | 0.454808 | 0.458505 |
| 7 | 0.304863 | 0.296802 | 0.30404 | 0.292384 | 0.213087 | 0.206271 | 0.216819 | 0.373078 | 0.455298 | 0.455755 | 0.460783 | 0.464056 |
predictions_df_90
| Over_dim 256 10_Targets | Over_dim 128 10_Targets | Over_dim 64 10_Targets | Over_dim 32 10_Targets | Over_dim 256 Mnist | Over_dim 128 Mnist | Over_dim 64 Mnist | Over_dim 32 Mnist | Over_dim 256 Noisy | Over_dim 128 Noisy | Over_dim 64 Noisy | Over_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.5718 | 0.5965 | 0.5888 | 0.6034 | 0.5416 | 0.5378 | 0.5469 | 0.4884 | 0.7299 | 0.7374 | 0.7429 | 0.7401 |
| 1 | 0.5447 | 0.5912 | 0.5718 | 0.6176 | 0.5401 | 0.5397 | 0.5408 | 0.4993 | 0.7488 | 0.7456 | 0.7487 | 0.7381 |
| 2 | 0.5435 | 0.5901 | 0.5711 | 0.6175 | 0.517 | 0.5229 | 0.5249 | 0.4839 | 0.7402 | 0.7357 | 0.7313 | 0.7133 |
| 3 | 0.5432 | 0.5898 | 0.571 | 0.6174 | 0.4857 | 0.5041 | 0.4949 | 0.4623 | 0.7254 | 0.7187 | 0.7107 | 0.69 |
| 4 | 0.5432 | 0.5898 | 0.571 | 0.6174 | 0.4518 | 0.4855 | 0.4613 | 0.4434 | 0.7079 | 0.7007 | 0.6889 | 0.6596 |
| 5 | 0.5432 | 0.5898 | 0.571 | 0.6174 | 0.4262 | 0.4624 | 0.4289 | 0.4278 | 0.6879 | 0.6809 | 0.6691 | 0.6341 |
| 6 | 0.5432 | 0.5898 | 0.571 | 0.6174 | 0.3996 | 0.4407 | 0.401 | 0.408 | 0.6714 | 0.6601 | 0.6477 | 0.6073 |
| 7 | 0.5432 | 0.5898 | 0.571 | 0.6174 | 0.3713 | 0.4245 | 0.3823 | 0.3937 | 0.6538 | 0.6378 | 0.631 | 0.5834 |
| Over_dim 256 10_Targets | Over_dim 128 10_Targets | Over_dim 64 10_Targets | Over_dim 32 10_Targets | Over_dim 256 Mnist | Over_dim 128 Mnist | Over_dim 64 Mnist | Over_dim 32 Mnist | Over_dim 256 Noisy | Over_dim 128 Noisy | Over_dim 64 Noisy | Over_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.447527 | 0.433355 | 0.434261 | 0.43263 | 0.230042 | 0.223261 | 0.273373 | 0.83954 | 0.697481 | 0.704799 | 0.70216 | 0.697246 |
| 1 | 0.493122 | 0.475556 | 0.489553 | 0.47067 | 0.240655 | 0.232978 | 0.285642 | 0.851326 | 0.719297 | 0.725511 | 0.72433 | 0.720446 |
| 2 | 0.495834 | 0.481226 | 0.495524 | 0.475611 | 0.256812 | 0.245764 | 0.300495 | 0.862435 | 0.736044 | 0.741245 | 0.743148 | 0.740992 |
| 3 | 0.495969 | 0.481864 | 0.495933 | 0.476184 | 0.273967 | 0.260116 | 0.316457 | 0.874526 | 0.750408 | 0.754961 | 0.759057 | 0.758151 |
| 4 | 0.496002 | 0.481898 | 0.495955 | 0.476237 | 0.291347 | 0.274944 | 0.332197 | 0.886893 | 0.763611 | 0.767535 | 0.773143 | 0.772987 |
| 5 | 0.496003 | 0.481898 | 0.495956 | 0.476247 | 0.309191 | 0.289398 | 0.347087 | 0.898773 | 0.775872 | 0.779171 | 0.785829 | 0.786064 |
| 6 | 0.496003 | 0.481898 | 0.495956 | 0.476248 | 0.327759 | 0.30368 | 0.361264 | 0.910405 | 0.787242 | 0.78996 | 0.797326 | 0.797622 |
| 7 | 0.496003 | 0.481898 | 0.495956 | 0.476248 | 0.345857 | 0.31797 | 0.374979 | 0.922309 | 0.797798 | 0.799962 | 0.807852 | 0.807835 |
| Over_dim 256 10_Targets | Over_dim 128 10_Targets | Over_dim 64 10_Targets | Over_dim 32 10_Targets | Over_dim 256 Mnist | Over_dim 128 Mnist | Over_dim 64 Mnist | Over_dim 32 Mnist | Over_dim 256 Noisy | Over_dim 128 Noisy | Over_dim 64 Noisy | Over_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.303588 | 0.295587 | 0.300221 | 0.292792 | 0.186282 | 0.180678 | 0.205833 | 0.486351 | 0.428019 | 0.425591 | 0.425603 | 0.427066 |
| 1 | 0.314437 | 0.304418 | 0.311361 | 0.298628 | 0.187338 | 0.183307 | 0.209192 | 0.489735 | 0.42559 | 0.42568 | 0.427311 | 0.429328 |
| 2 | 0.315057 | 0.305581 | 0.312647 | 0.299519 | 0.193433 | 0.188887 | 0.215389 | 0.493981 | 0.430511 | 0.431384 | 0.434057 | 0.43683 |
| 3 | 0.315085 | 0.305711 | 0.312735 | 0.299616 | 0.200949 | 0.195839 | 0.222714 | 0.499235 | 0.436952 | 0.437991 | 0.441371 | 0.444623 |
| 4 | 0.315093 | 0.305714 | 0.31274 | 0.299627 | 0.209029 | 0.203246 | 0.230174 | 0.504852 | 0.443621 | 0.444541 | 0.448395 | 0.451811 |
| 5 | 0.315093 | 0.305712 | 0.31274 | 0.299629 | 0.2176 | 0.210542 | 0.23733 | 0.510325 | 0.450097 | 0.450753 | 0.454946 | 0.458281 |
| 6 | 0.315093 | 0.305712 | 0.31274 | 0.299629 | 0.226634 | 0.217778 | 0.244208 | 0.515746 | 0.456227 | 0.456556 | 0.461013 | 0.464046 |
| 7 | 0.315093 | 0.305712 | 0.31274 | 0.299629 | 0.235464 | 0.225 | 0.250876 | 0.521326 | 0.461984 | 0.461935 | 0.466633 | 0.469157 |
predictions_df_100
| Over_dim 256 10_Targets | Over_dim 128 10_Targets | Over_dim 64 10_Targets | Over_dim 32 10_Targets | Over_dim 256 Mnist | Over_dim 128 Mnist | Over_dim 64 Mnist | Over_dim 32 Mnist | Over_dim 256 Noisy | Over_dim 128 Noisy | Over_dim 64 Noisy | Over_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.4859 | 0.506 | 0.5034 | 0.5187 | 0.4407 | 0.446 | 0.4479 | 0.3651 | 0.6231 | 0.6355 | 0.6417 | 0.6449 |
| 1 | 0.4626 | 0.5019 | 0.4839 | 0.5264 | 0.4409 | 0.4498 | 0.4491 | 0.3749 | 0.6436 | 0.6459 | 0.6549 | 0.6454 |
| 2 | 0.4618 | 0.5007 | 0.4833 | 0.5273 | 0.4154 | 0.4354 | 0.4324 | 0.362 | 0.6402 | 0.6351 | 0.6396 | 0.6275 |
| 3 | 0.4617 | 0.5008 | 0.4832 | 0.5273 | 0.3805 | 0.4184 | 0.4065 | 0.3467 | 0.6256 | 0.6193 | 0.6165 | 0.6051 |
| 4 | 0.4617 | 0.5009 | 0.4832 | 0.5273 | 0.3583 | 0.3993 | 0.3827 | 0.3375 | 0.6122 | 0.6038 | 0.5968 | 0.5816 |
| 5 | 0.4617 | 0.5009 | 0.4832 | 0.5273 | 0.3386 | 0.3841 | 0.361 | 0.3238 | 0.5984 | 0.5873 | 0.5826 | 0.5614 |
| 6 | 0.4617 | 0.5009 | 0.4832 | 0.5273 | 0.3196 | 0.365 | 0.3371 | 0.3114 | 0.5848 | 0.5716 | 0.5659 | 0.5411 |
| 7 | 0.4617 | 0.5009 | 0.4832 | 0.5273 | 0.3033 | 0.3507 | 0.3182 | 0.3022 | 0.57 | 0.5543 | 0.5505 | 0.5229 |
| Over_dim 256 10_Targets | Over_dim 128 10_Targets | Over_dim 64 10_Targets | Over_dim 32 10_Targets | Over_dim 256 Mnist | Over_dim 128 Mnist | Over_dim 64 Mnist | Over_dim 32 Mnist | Over_dim 256 Noisy | Over_dim 128 Noisy | Over_dim 64 Noisy | Over_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.457922 | 0.445219 | 0.442727 | 0.444097 | 0.320075 | 0.281777 | 0.409031 | 1.29169 | 0.716855 | 0.724989 | 0.720663 | 0.713318 |
| 1 | 0.507736 | 0.491609 | 0.506161 | 0.488082 | 0.33349 | 0.293716 | 0.423896 | 1.30406 | 0.741463 | 0.74796 | 0.744427 | 0.737835 |
| 2 | 0.510967 | 0.498368 | 0.513313 | 0.494043 | 0.349804 | 0.306674 | 0.437016 | 1.31229 | 0.759178 | 0.764115 | 0.763777 | 0.75855 |
| 3 | 0.511109 | 0.499124 | 0.513858 | 0.494734 | 0.366513 | 0.320587 | 0.451261 | 1.32136 | 0.773472 | 0.777391 | 0.779603 | 0.77506 |
| 4 | 0.51114 | 0.499189 | 0.513886 | 0.494783 | 0.383785 | 0.334074 | 0.465205 | 1.33067 | 0.786134 | 0.789175 | 0.793398 | 0.788879 |
| 5 | 0.511141 | 0.499199 | 0.513887 | 0.494793 | 0.399847 | 0.347596 | 0.478667 | 1.33989 | 0.79775 | 0.799889 | 0.805609 | 0.800847 |
| 6 | 0.511141 | 0.499199 | 0.513887 | 0.494793 | 0.41641 | 0.361261 | 0.492031 | 1.34929 | 0.808491 | 0.809692 | 0.816547 | 0.811424 |
| 7 | 0.511141 | 0.499199 | 0.513887 | 0.494794 | 0.432526 | 0.374627 | 0.504573 | 1.35817 | 0.818397 | 0.818759 | 0.826485 | 0.820806 |
| Over_dim 256 10_Targets | Over_dim 128 10_Targets | Over_dim 64 10_Targets | Over_dim 32 10_Targets | Over_dim 256 Mnist | Over_dim 128 Mnist | Over_dim 64 Mnist | Over_dim 32 Mnist | Over_dim 256 Noisy | Over_dim 128 Noisy | Over_dim 64 Noisy | Over_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.311086 | 0.30388 | 0.308116 | 0.300863 | 0.234037 | 0.212806 | 0.275581 | 0.709781 | 0.443402 | 0.4407 | 0.44 | 0.440715 |
| 1 | 0.322517 | 0.313381 | 0.320681 | 0.308275 | 0.235875 | 0.21629 | 0.279897 | 0.713696 | 0.440435 | 0.440198 | 0.440829 | 0.441332 |
| 2 | 0.323202 | 0.314762 | 0.322179 | 0.309368 | 0.241789 | 0.22172 | 0.284978 | 0.716584 | 0.444778 | 0.445199 | 0.446824 | 0.447719 |
| 3 | 0.323227 | 0.31491 | 0.322303 | 0.309489 | 0.248855 | 0.228247 | 0.291244 | 0.720317 | 0.45057 | 0.451072 | 0.453548 | 0.454567 |
| 4 | 0.323236 | 0.314918 | 0.32231 | 0.3095 | 0.25663 | 0.234812 | 0.297618 | 0.724376 | 0.456565 | 0.456908 | 0.460072 | 0.460908 |
| 5 | 0.323236 | 0.314921 | 0.32231 | 0.309502 | 0.264133 | 0.241481 | 0.303912 | 0.728489 | 0.462411 | 0.462442 | 0.466154 | 0.466612 |
| 6 | 0.323236 | 0.314921 | 0.32231 | 0.309502 | 0.272014 | 0.248242 | 0.310192 | 0.732746 | 0.467977 | 0.467584 | 0.47177 | 0.471733 |
| 7 | 0.323236 | 0.314921 | 0.32231 | 0.309502 | 0.27977 | 0.25487 | 0.316111 | 0.736763 | 0.473196 | 0.472361 | 0.476962 | 0.476325 |